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EY (Ernst & Young)
Original title: The valuation of crypto-assets Minds made for shaping financial services
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Different from the traditional financial industry, cryptocurrency asset valuation is a new field. Business valuation needs to consider factors such as income, expenses, capital, taxable income, profits, shareholders and stakeholders. However, the value of cryptocurrencies needs to be evaluated from a new perspective. Many people try to use traditional financial industry valuation methods to estimate encrypted assets, but the results are not satisfactory. Therefore, the valuation of cryptocurrencies is a topic worth studying. This issue will explain a security token valuation model.
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Security tokens
Decision rights are not the same as distribution rights associated with ownership of different security tokens, but one fundamental characteristic is common to all: the right to receive future distributions. Traditional valuation methods such as the market approach and the income approach can be used in this case.
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market approach
The market valuation method adopted for a given token depends on its liquidity and stage development. Relevant scenarios include tokens at launch, from an illiquid token with no directly observable price, to a token with continuous updates and a trading pair directly with fiat currencies.
Quoted price
Token secondary transaction pricing is an important reference to assess the key to market value. Typically, there is not one dominant market as tokens tend to trade on multiple exchanges, but there may still be many active markets.
It is important to consider liquidity and transaction depth, but it is also a matter of judgment - both in terms of application threshold and evaluation means. Namely, whether a particular token is easily convertible into another crypto asset (even a highly liquid cryptocurrency such as Bitcoin or Ethereum), or directly into fiat currency.
The premise is that the token shows sufficient liquidity in direct trading with fiat currency trading pairs, and we will consider reasonably adopting the quotation as its token market value. Such treatment should also be consistent with the accounting fair value hierarchy. However, due to recent coin volatility, cryptocurrency prices do illustrate that market values may differ from "fundamental value."
Where tokens cannot be reliably converted directly into fiat currencies (i.e., such realization requires one or more intermediate conversions, or "jumps," into crypto-assets with direct fiat trading pairs), or in illiquid In some cases, we will consider applying discounts due to lack of liquidity.
Comparable tokens
In cases where there is no secondary transaction pricing or the liquidity is too weak to be priced, the token can be compared to the most recently incubated tokens or tokens with liquidity pricing by relying on the market.
Applying valuation multiples is challenging because financial metrics such as revenue or earnings are often not sufficiently comparable between assets. Liquid security tokens are relatively scarce in our observations, and comparisons to quoted companies or companies that have recently sold raise conceptual issues due to the maturity and risk of revenue stream sources.
Another approach is to consider the total value of the major tokens issued by the capitalization achieved by the token market in recent comparable ICOs, similar to the benchmarking approach used to value companies that raised venture capital in the early stages.
Comparability can be assessed on the basis of a scorecard approach, usually used in the early stages of VC investments. The scorecard project includes the technical and commercial development of the project in the track, the quality and experience of the team behind the project, the size of the target market and the uniqueness of the project. This approach may yield a relatively wide and indicative range of values.
Income approach (income approach)
The income approach, based on the cash flows of security token holders, is conceptually the best way to assess fundamental value. This method is useful when making investment decisions when market prices are influenced by market inefficiencies, sentiment and speculation. However, this approach may not be consistent with the requirements of market-based valuation methods such as financial reporting and taxation.
Forecastdot.comTraditional start-ups tend to be overly optimistic and their predictions can easily fail. For example, research by the European Investment Fund shows that approximately 57% of early-stage venture capital investments have a return on money multiples (MoM) of less than 0.25x. AutonomousNEXT Research Shows Kickstarter Projects, Pre-Series A Startups and
The failure rates for companies 10 years after their IPO are 65%, 70% and 85%, respectively. According to the latter source, ICOs to date have shown a failure rate of around 50%. EY research, Initial Coin Offerings (ICOs): 2017 offerings, found 86% of ICOs were trading below their listing price a year later.
Still, optimism remains high, especially among staunch supporters of many crypto assets. Therefore, we encourage analysis of the size of each project's target market and its share. A consensus view on market developments should be given due consideration in the scenario analysis and its possible application.
Discount rates
The discount rate is the key assumption of the income approach. Yet their estimates of early-stage business investment are highly subjective. Determining an appropriate discount rate using the traditionally accepted Capital Asset Pricing Model (CAPM) is very challenging. This is because market data (e.g. beta) are unobservable, since comparable public companies do not exist, and judgmental alpha risk premium assumptions are required.
One solution is to estimate the discount rate based on the lowest rate of return VC investors receive from survey data or published returns. Some large pension funds in the United States publish a relatively large amount of income data. Such data may not be representative of the entire market. Additionally, alternative investment performance metrics often rely on self-reported data and may thus contain inherent biases, such as survivorship bias. Even with good data available, estimating required rates of return using internal rate of return (IRR) and MoMs, along with return distributions, is subjective.
These factors may include funding risk (e.g., will the project be fully funded over its expected life cycle, or will further financing be required? If so, what are the risks of obtaining Clear ownership and protection regarding capital property rights?) and upfront participant commitments (eg, upfront participation of participants can be considered to reduce the commercial risk of the project). When evaluating these qualitative factors, the range of discount rates can be narrowed so that it can better reflect the specific risks of related projects.
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Another approach is to use a scenario-based structure to construct modeling of future cash flows. This allows the risk exposure of the project to be separated from extreme cases, such as the probability of failure or unicorn companies (over 1 billion US dollars), and a relatively normal discount rate can then be derived using the CAPM, which reflects the comparison with the same geographical And the risk of listed companies in the terminal market risk. In a decentralized fog computing platform, such as SONM, this may mean comparisons with cloud computing providers. Scenario probabilities can be estimated by reference to the distribution of returns observed in VC as described above.
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When constructing a valuation under the income approach, it is important to consider the specific nature of each project. To illustrate this point, note the difference between, for example, a DAO and a SONM, where the former approximates a normal company managed via a blockchain, and the latter requires some separate analysis of the developer entity's ability to sustain its long-term activity. This affects how we model the risk of failure in each case.
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